Literature DB >> 15779835

Model-based prediction of expiratory resistance index in patients with asthma.

Ofer Barnea1, Shimon Abboud, Alexander Guber, Israel Bruderman.   

Abstract

OBJECTIVES: Develop a sensitive algorithm and index for detection of asthma patients using forced expiratory flow curves.
METHODS: A lumped-parameter model of forced expiration was developed. The model can predict the flow-volume curve during forced expiratory maneuver. The flow-volume curves generated by the model depend on values of resistance parameters (FER). Use of flow-volume curves recorded from normal subjects and from patients with asthma before and after ventolin inhalation as inputs for the inverse model, yielded the resistance parameters for each case. These parameters are based on the entire information presented in the flow-volume curve and on the reduction in flow at all lung volumes.
RESULTS: Forced Expiratory Resistance (FER(N)) indices were estimated at different percent of lung volumes using the inverse model. The index was significantly affected by inhalation of ventolin in asthmatic patients and was insensitive to ventolin inhalation in normal patients. In asthmatic patients, the FER index at five lung volumes (out of eight), was two--five times greater than in normal subjects with p < 0.05 (three of them with p < 0.01).
CONCLUSIONS: The estimated parameters were sensitive indicators of the degree of lung function impairment and were able to accurately distinguish between healthy and asthmatic patients.

Entities:  

Mesh:

Year:  2004        PMID: 15779835     DOI: 10.1007/s10877-005-9612-5

Source DB:  PubMed          Journal:  J Clin Monit Comput        ISSN: 1387-1307            Impact factor:   2.502


  8 in total

1.  Theoretical considerations of the bronchial pressure-flow-volume relationships with particular reference to the maximum expiratory flow volume curve.

Authors:  D L FRY
Journal:  Phys Med Biol       Date:  1958-10       Impact factor: 3.609

2.  New model-based indices for maximum expiratory flow-volume curve in patients with chronic obstructive pulmonary disease.

Authors:  O Barnea; S Abboud; A Guber; I Bruderman
Journal:  Comput Biol Med       Date:  1996-03       Impact factor: 4.589

3.  Expiratory flow rates, driving pressures and time dependent factors, simulation by means of a model.

Authors:  J Clément; J Pardaens; K P Van de Woestijne
Journal:  Respir Physiol       Date:  1974-06

4.  A physical model of expiration.

Authors:  J Pardaens; K P Van de Woestijne; J Clément
Journal:  J Appl Physiol       Date:  1972-10       Impact factor: 3.531

5.  A preliminary lung model for simulating the aerodynamics of the bronchial tree.

Authors:  D L Fry
Journal:  Comput Biomed Res       Date:  1968-10

6.  A computational model for expiratory flow.

Authors:  R K Lambert; T A Wilson; R E Hyatt; J R Rodarte
Journal:  J Appl Physiol Respir Environ Exerc Physiol       Date:  1982-01

7.  Steady pressure-flow relationship of a model of the canine bronchial tree.

Authors:  D B Reynolds; J S Lee
Journal:  J Appl Physiol Respir Environ Exerc Physiol       Date:  1981-11

8.  Maximum expiratory flow-volume curve: mathematical model and experimental results.

Authors:  S Abboud; O Barnea; A Guber; N Narkiss; I Bruderman
Journal:  Med Eng Phys       Date:  1995-07       Impact factor: 2.242

  8 in total
  1 in total

1.  Detection of obstructive respiratory abnormality using flow-volume spirometry and radial basis function neural networks.

Authors:  Mahesh Veezhinathan; Swaminathan Ramakrishnan
Journal:  J Med Syst       Date:  2007-12       Impact factor: 4.460

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.